January 10, 2023
After a number of delays, Intel has launched its fourth-generation Intel Xeon Scalable processor, codenamed Sapphire Rapids, the successor to Ice Lake. Manufact Read more…
November 9, 2022
Ahead of SC22 (next week!), Intel today announced a major rebrand of its forthcoming datacenter-focused products. In short: the fourth-generation Xeon CPU with Read more…
September 28, 2021
In support of the Department of Energy’s National Nuclear Security Administration (NNSA), the Tri-Lab CTS-2 system contract award was announced last week. The NNSA TriLab partnership – comprising Livermore, Los Alamos and Sandia national labs – awarded Dell Technologies... Read more…
November 16, 2020
Nvidia has doubled the memory of its previous supercomputing GPUs with its new A100 80GB GPU, which aims to drive new levels of supercomputing performance in a wide variety of uses, from AI and ML research to engineering and more. The new A100 80GB GPU comes just six months... Read more…
Today, manufacturers of all sizes face many challenges. Not only do they need to deliver complex products quickly, they must do so with limited resources while continuously innovating and improving product quality. With the use of computer-aided engineering (CAE), engineers can design and test ideas for new products without having to physically build many expensive prototypes. This helps lower costs, enhance productivity, improve quality, and reduce time to market.
As the scale and scope of CAE grows, manufacturers need reliable partners with deep HPC and manufacturing expertise. Together with AMD, HPE provides a comprehensive portfolio of high performance systems and software, high value services, and an outstanding ecosystem of performance optimized CAE applications to help manufacturing customers reduce costs and improve quality, productivity, and time to market.
Read this whitepaper to learn how HPE and AMD set a new standard in CAE solutions for manufacturing and can help your organization optimize performance.
A workload-driven system capable of running HPC/AI workloads is more important than ever. Organizations face many challenges when building a system capable of running HPC and AI workloads. There are also many complexities in system design and integration. Building a workload driven solution requires expertise and domain knowledge that organizational staff may not possess.
This paper describes how Quanta Cloud Technology (QCT), a long-time Intel® partner, developed the Taiwania 2 and Taiwania 3 supercomputers to meet the research needs of the Taiwan’s academic, industrial, and enterprise users. The Taiwan National Center for High-Performance Computing (NCHC) selected QCT for their expertise in building HPC/AI supercomputers and providing worldwide end-to-end support for solutions from system design, through integration, benchmarking and installation for end users and system integrators to ensure customer success.
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